Acoustic scene classification (ASC) has gained significant interest recently due to its diverse
applications. Various audio signal processing and machine learning methods have been …

Audio pattern recognition is an important research topic in the machine learning area, and
includes several tasks such as audio tagging, acoustic scene classification, music …

Birds may need to be identified for purposes such as environmental monitoring, follow-up,
and species detection in the ecological area. Automatic sound classifiers have been used to …

Dynamical theories of speech processing propose that the auditory cortex parses acoustic
information in parallel at the syllabic and phonemic timescales. We developed a paradigm to …

What is the function of auditory hemispheric asymmetry? We propose that the identification
of sound sources relies on the asymmetric processing of two complementary and …

Health care, public safety, home security and self-driving cars applications rely on the
automatic identification and interpretation of sound events. For example, abnormal …

This paper presents the Synthetic Polyphonic Ambient Sound Source (SPASS) dataset, a
publicly available synthetic polyphonic audio dataset. SPASS was designed to train deep …

Environmental noise in urban settings has several adverse effects on the population's health
and quality of life. Detecting and classifying sound sources is a primary task to control this …

The human auditory system is designed to capture and encode sounds from our
surroundings and conspecifics. However, the precise mechanisms by which it adaptively …

We study the usability of pre-trained weakly supervised audio tagging (AT) models as
feature extractors for general audio representations. We mainly analyze the feasibility of …